Azure-Samples / Azure-Samples/azure-search-python-samples

Azure Agentic retrieval fails with unhelpful error response in spite of correct setup

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Jupyter Notebook
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描述

When using the [example python notebook provided for agentic search](https://github.com/Azure-Samples/azure-search-python-samples/tree/main/Quickstart-Agentic-Retrieval), after having configured everything correctly, I get the following response:

```
HttpResponseError Traceback (most recent call last)
[](https://localhost:8080/#) in ()
12 })
13
---> 14 retrieval_result = agent_client.retrieve(
15 retrieval_request=KnowledgeAgentRetrievalRequest(
16 messages=[KnowledgeAgentMessage(role=msg["role"], content=[KnowledgeAgentMessageTextContent(text=msg["content"])]) for msg in messages if msg["role"] != "system"],

3 frames
[/usr/local/lib/python3.11/dist-packages/azure/search/documents/agent/_generated/operations/_knowledge_retrieval_operations.py](https://localhost:8080/#) in retrieve(self, retrieval_request, x_ms_query_source_authorization, request_options, **kwargs)
219 map_error(status_code=response.status_code, response=response, error_map=error_map)
220 error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
--> 221 raise HttpResponseError(response=response, model=error)
222
223 deserialized = self._deserialize("KnowledgeAgentRetrievalResponse", pipeline_response.http_response)

HttpResponseError: () An error has occurred.
Code:
Message: An error has occurred.
```

### Steps I followed:
- Clone the notebook
- Created the AI search index on the "Standard" tier
- Created an Open AI service
- Created the gpt-4o deployment
- Used `text-embedding-3-large` embedding
- Added the following permissions for the user - Search Service Contributor, Search Index Data Contributor, Search Index Data Reader
- Added all the necessary keys
- Executed your notebook code

贡献指南

打开贡献指南

调研方向

首先使用 issue 中列出的设置详细信息(Search tier、OpenAI deployment、embedding model、permissions 和 keys),通过 agent_client.retrieve 调用重新运行 Quickstart-Agentic-Retrieval notebook。将失败的请求与 notebook 配置进行比较。当示例完成检索,或提供具体且可操作的错误而不是通用的 HttpResponseError 时,即表示完成。

由索引模型根据 Issue 内容生成。

评估

技术栈
azure, jupyter-notebook, python
领域
ai, cloud, search
Issue 类型
缺陷
难度
3/5
预计耗时
1-2 天
活跃度
停滞
描述清晰度
基本清楚
新手友好度
35/100

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